ArticlePloS one2017
Feasibility of large-scale deployment of multiple wearable sensors in Parkinson's disease.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers, 6 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
90 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- Continuous Movement Monitoring at Home Through Wearable Devices: A Systematic Review.Sensors (Basel, Switzerland) · 2025Pooled it
- Movement Disorders and Smart Wrist Devices: A Comprehensive Study.Sensors (Basel, Switzerland) · 2025Pooled it
- A systematic review of methods used to conduct decentralised clinical trials.British journal of clinical pharmacology · 2022Pooled it
- Wearables in the home-based assessment of abnormal movements in Parkinson's disease: a systematic review of the literature.Journal of neurology · 2022Pooled it
- Assessing the usability of wearable devices to measure gait and physical activity in chronic conditions: a systematic review.Journal of neuroengineering and rehabilitation · 2021Pooled it
- Systematic Review Looking at the Use of Technology to Measure Free-Living Symptom and Activity Outcomes in Parkinson's Disease in the Home or a Home-like Environment.Journal of Parkinson's disease · 2020Pooled it
- Real-world data capture of daily limb loading using force-sensing insoles: Feasibility and lessons learned.Journal of biomechanics · 2024Trial
- Trial
- Real-Time Kinematic Adaptive Deep Brain Stimulation Safely Reduces Gait Impairment and Freezing of Gait in Parkinson's Disease.medRxiv : the preprint server for health sciences · 2026Article
- Added value of a wrist-worn device for assessing tremor in Parkinson's disease: reliability and validity of tremor evaluation at home.NPJ Parkinson's disease · 2025Article
- Optimizing wrist-worn wearable compliance with insights from two Parkinson's disease cohort studies.NPJ Parkinson's disease · 2025Article
- Digital Biomarkers for Parkinson Disease: Bibliometric Analysis and a Scoping Review of Deep Learning for Freezing of Gait.Journal of medical Internet research · 2025Article
- Improving recruitment and retention of people with Parkinson's disease to clinical studies: A scoping review.Journal of Parkinson's disease · 2025Article
- Gait characteristics in people with Friedreich ataxia: daily life versus clinic measures.Frontiers in neurology · 2025Article
- Editorial: Digital biomarkers in movement disorders.Frontiers in neurology · 2025Article
- Patient Experience and Feasibility of a Remote Monitoring System in Parkinson's Disease.Movement disorders clinical practice · 2024Observational
- Assessing the clinical utility of inertial sensors for home monitoring in Parkinson's disease: a comprehensive review.NPJ Parkinson's disease · 2024Article
- The digital signature of emergent tremor in Parkinson's disease.NPJ Parkinson's disease · 2024Article
- Digital biomarkers for non-motor symptoms in Parkinson's disease: the state of the art.NPJ digital medicine · 2024Review
- Assisted technology in Parkinson's disease gait: what's up?Arquivos de neuro-psiquiatria · 2024Review
30 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
Wearable devices can capture objective day-to-day data about Parkinson's Disease (PD). This study aims to assess the feasibility of implementing wearable technology to collect data from multiple sensors during the daily lives of PD patients. The Parkinson@home study is an observational, two-cohort (North America, NAM; The Netherlands, NL) study. To recruit participants, different strategies were used between sites. Main enrolment criteria were self-reported diagnosis of PD, possession of a smartphone and age≥18 years. Participants used the Fox Wearable Companion app on a smartwatch and smartphone for a minimum of 6 weeks (NAM) or 13 weeks (NL). Sensor-derived measures estimated information about movement. Additionally, medication intake and symptoms were collected via self-reports in the app. A total of 953 participants were included (NL: 304, NAM: 649). Enrolment rate was 88% in the NL (n = 304) and 51% (n = 649) in NAM. Overall, 84% (n = 805) of participants contributed sensor data. Participants were compliant for 68% (16.3 hours/participant/day) of the study period in NL and for 62% (14.8 hours/participant/day) in NAM. Daily accelerometer data collection decreased 23% in the NL after 13 weeks, and 27% in NAM after 6 weeks. Data contribution was not affected by demographics, clinical characteristics or attitude towards technology, but was by the platform usability score in the NL (χ2 (2) = 32.014, p<0.001), and self-reported depression in NAM (χ2(2) = 6.397, p = .04). The Parkinson@home study shows that it is feasible to collect objective data using multiple wearable sensors in PD during daily life in a large cohort.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.